Computer Science & Statistics

Controlling Privacy Loss in Sampling Schemes: An Analysis of Stratified and Cluster Sampling
with Mark Bun, Jörg Drechsler, Marco Gaboardi, and Audra McMillan 
To appear in Foundations of Responsible Computing (FORC), 2022.
with Jörg Drechsler, Ira Globus-Harris, Audra McMillan, and Adam Smith
Theory and Practice of Differential Privacy (TPDP), 2021.
To appear in Journal of Survey Statistics and Methodology (JSSAM), 2022.
Differentially Private Simple Linear Regression
with Daniel Alabi, Audra McMillan, Adam Smith, and Salil Vadhan
Theory and Practice of Differential Privacy (TPDP), 2020.
To appear in Proceedings on Privacy Enhancing Technologies (PoPETs), 2022.
Analyzing the Differentially Private Theil-Sen Estimator for Simple Linear Regression
with Salil Vadhan
Theory and Practice of Differential Privacy (TPDP), 2021.

Technology & Society

with danah boyd
To appear in Harvard Data Science Review, 2022.
Privacy Law Scholars Conference, 2021.
with Catherine Kerner
Computation+Journalism Conference, 2021.
‘Time Capsule’ Archiving Through Strong Dark Archives (SDA): Designing Trustable Distributed Archives for Sensitive Materials
with John Bowers, Jack Cushman, and Jonathan Zittrain
Digital Library Federation Forum, 2020.
DIMACS Workshop on Co-Development of Computer Science and Law, 2020.


with Kenneth Michelson, Chris Rees, Paige VonAchen, Michael Wornow, Michael Monuteaux, and Mark Neuman
Clinical Infectious Diseases, 2020.
with Benedikt Bünz and Mariana Raykova
Working paper, last updated in 2020